Power circuit component optimization method based on orthogonal learning particle swarm

Abstract

The invention discloses a power circuit component optimization method based on an orthogonal learning particle swarm, and belongs to the power electronic technology and the field of computational intelligence. An orthogonal learning particle swarm optimization with a mutation strategy is used for carrying out optimization on an optimal component design of a power electronic circuit. Firstly, a method of generating a new optimal learning object based on an orthogonal combination mode is designed, and is used for mining information of a historical optimal solution of a particle individual and information of a globally-optimal solution of a swarm in the orthogonal learning particle swarm optimization, and combining a learning object which can guide particles to develop in a better direction, secondly, a mutation operator which can improve diversity of the orthogonal learning particle swarm optimization is designed, and the defect that the orthogonal learning particle swarm optimization easily falls into local optimum is overcome. All components of the power electronic circuit serve as variables needing to be optimized and are coded into individuals of the orthogonal learning particle swarm optimization, optimization is carried out on values of the components of the power electronic circuit through specific optimization processes such as update of the speed, update of the location, mutation operation and update of the optimal learning object of the orthogonal learning particle swarm optimization, and the power circuit component optimization method based on the orthogonal learning particle swarm has important application value in the existing large-scale circuit design and optimization field.

Description

Technical field: [0001] The invention relates to the two fields of power electronic circuits and computational intelligence, in particular to a power circuit component optimization method based on an orthogonal learning particle swarm algorithm. technical background: [0002] Since the emergence of power semiconductor devices in 1950, power electronic circuits have developed rapidly and have become an important technology in many fields such as industry, commerce, housing, aerospace, military and public utilities. The modeling, design and analysis of power electronic circuits is a fundamental and important research field in electronics. Power electronic circuits are usually made up of many constituent elements, such as resistors, capacitors and inductors. These electrical components need to be optimized to ensure that the final circuit can obtain better circuit performance. As the scale of power electronic circuits continues to increase, proper component design and paramet...

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Problems solved by technology

However, in practical applications, genetic algorithms and ant colony algorithms still have many disadvantages, such as the need to consume a lot of calculations to find relatively better circuit component values, while the traditional particle swarm algorithm is often unable to find global optimal solution

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